The deepseek-vl2-tiny gets the wrong output

`import torch
from transformers import AutoModelForCausalLM

from deepseek_vl2.models import DeepseekVLV2Processor, DeepseekVLV2ForCausalLM
from deepseek_vl2.utils.io import load_pil_images

# specify the path to the model
model_path = "/whut_data/Yujg/DeepSeek-VL2/deepseek-vl2-tiny"
vl_chat_processor: DeepseekVLV2Processor = DeepseekVLV2Processor.from_pretrained(model_path)
tokenizer = vl_chat_processor.tokenizer

vl_gpt = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True, torch_dtype=torch.bfloat16)
vl_gpt = vl_gpt.to(torch.bfloat16).cuda().eval()

## single image conversation example
conversation = [
{
"role": "<|User|>",
"content": "\nDescribe the image.",
"images": ["/whut_data/Yujg/DeepSeek-VL2/images/visual_grounding_1.jpeg"],
},
{"role": "<|Assistant|>", "content": ""},
]

# load images and prepare for inputs
pil_images = load_pil_images(conversation)
prepare_inputs = vl_chat_processor(
conversations=conversation,
images=pil_images,
force_batchify=True,
system_prompt=""
).to(vl_gpt.device)

# run image encoder to get the image embeddings
inputs_embeds = vl_gpt.prepare_inputs_embeds(**prepare_inputs)

# run the model to get the response
outputs = vl_gpt.language_model.generate(
inputs_embeds=inputs_embeds,
attention_mask=prepare_inputs.attention_mask,
pad_token_id=tokenizer.eos_token_id,
bos_token_id=tokenizer.bos_token_id,
eos_token_id=tokenizer.eos_token_id,
max_new_tokens=512,
do_sample=False,
use_cache=True
)

answer = tokenizer.decode(outputs[0].cpu().tolist(), skip_special_tokens=True)
print(f"{prepare_inputs['sft_format'][0]}", answer)`

and I get this:
`Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Add pad token = ['<｜▁pad▁｜>'] to the tokenizer
<｜▁pad▁｜>:2
Add image token = [''] to the tokenizer
:128815
Add grounding-related tokens = ['<|ref|>', '<|/ref|>', '<|det|>', '<|/det|>', '<|grounding|>'] to the tokenizer with input_ids
<|ref|>:128816
<|/ref|>:128817
<|det|>:128818
<|/det|>:128819
<|grounding|>:128820
Add chat tokens = ['<|User|>', '<|Assistant|>'] to the tokenizer with input_ids
<|User|>:128821
<|Assistant|>:128822`

I can't find a way to fix it!!